Impulsive control strategy for the Mittag-Leffler synchronization of fractional-order neural networks with mixed bounded and unbounded delays

Ivanka Stamova; Gani Stamov; Ivanka Stamova; Gani Stamov

doi:10.3934/math.2021138

AIMS Mathematics

2021, Volume 6, Issue 3: 2287-2303. doi: 10.3934/math.2021138

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Impulsive control strategy for the Mittag-Leffler synchronization of fractional-order neural networks with mixed bounded and unbounded delays

Ivanka Stamova ^{1
,
,},
Gani Stamov ²

1.
Department of Mathematics, University of Texas at San Antonio, San Antonio, TX 78249, USA
2.
Department of Mathematics, Technical University of Sofia, Bulgaria

Received: 09 November 2020 Accepted: 11 December 2020 Published: 15 December 2020
MSC : 26A33, 34K37, 34K45, 34K25, 34K60

In this paper we apply an impulsive control method to keep the Mittag-Leffler stability properties for a class of Caputo fractional-order cellular neural networks with mixed bounded and unbounded delays. The impulsive controls are realized at fixed moments of time. Our results generalize some known criteria to the fractional-order case and provide a design method of impulsive control law for the impulse free fractional-order neural network model. Examples are presented to demonstrate the effectiveness of our results.
- global Mittag-Leffler synchronization,
- neural networks,
- fractional-order derivatives,
- mixed delays,
- impulsive control
Citation: Ivanka Stamova, Gani Stamov. Impulsive control strategy for the Mittag-Leffler synchronization of fractional-order neural networks with mixed bounded and unbounded delays[J]. AIMS Mathematics, 2021, 6(3): 2287-2303. doi: 10.3934/math.2021138

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Abstract

In this paper we apply an impulsive control method to keep the Mittag-Leffler stability properties for a class of Caputo fractional-order cellular neural networks with mixed bounded and unbounded delays. The impulsive controls are realized at fixed moments of time. Our results generalize some known criteria to the fractional-order case and provide a design method of impulsive control law for the impulse free fractional-order neural network model. Examples are presented to demonstrate the effectiveness of our results.

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